Data Masking: Are there ways around your security policies?

Many ways, and in some cases may even improve your default security posture without additional action on your part, automatic data masking protects sensitive data without violating any security policy. Furthermore, masking and storing the data in parts ensure that while the data makes sense internally, it remains anonymous to a hacker.

These controls include anti-malware, siem and log management, endpoint protection solutions, encryption, data masking, and any other applicable security tool or technology responsible for securing data and detecting data breaches, data security tools include identity and access management, data loss prevention (DLP), anti-malware and anti-virus, security information and event management (SIEM) and data masking software. As a rule, within a large organization there are policies around naming conventions, handling of sensitive data, disaster recovery and other legal restrictions which a solution architect has to be mindful of when developing the solution.

The main reason for applying masking to a data field is to protect data that is classified as personal identifiable data, personal sensitive data or commercially sensitive data, however the data must remain usable for the purposes of undertaking valid test cycles, encryption can be used when data needs to be protected at rest and in use, while enabling certain users to reverse the encryption and get the original data back, for example, dynamic data masking implements the centralised policy of hiding or changing the sensitive data in a database that is inherited by any application wishes to access the data.

Driven Requirements

In addition to improving security and addressing compliance requirements, data masking is an effective way to mitigate the growing risk of insider threats, it teams are oftentimes faced with complex challenges regarding enterprise-wide data security, and a clearly articulated, policy-driven data masking technique can ease implementation and reduce cost. In the meantime, thales provides your organization with security and trust in data wherever data is created, shared or stored without impacting business agility.

Distinct from data masking, data encryption translates data into another form, or code, so that only people with access to a secret key (formally called a decryption key) or password can read it, traditional methods of security measures should also include encryption and data masking. By the way, your data governance program clearly outlines policies, procedures, responsibilities, and controls surrounding data activities.

Others Part

What you are seeing now where more controls that are kind of aimed towards helping organizations preserve the usefulness of that data while protecting the privacy of individuals, if your goal is to work quickly, and you are using tools that help you move quickly, you need to be mindful of the threat surface created with new tools and new ways of working. As a result, some are included as part of the database package, some are open source, and others come from security vendors.

Be careful of storing any sensitive data in the cache (or encrypt sensitive data that is stored in cache), while perimeter security solutions can make it more difficult to access the data from the outside, once the network is breached your data is only as safe as the data encryption you employ, also. And also, depending on your data access patterns, there may be times when you need tighter data security and access restrictions.

Once that is set, monitoring and auditing user activity and data access on business application and analytics environments enables meet the right of access requirement, another feature of the tool is self-heal of virtual test data that increases the viability of virtual test data. Also, on one hand, software-based security solutions encrypt the data to protect it from theft, on the other, hardware-based solutions can prevent read and write access to data.

Want to check how your Data Masking Processes are performing? You don’t know what you don’t know. Find out with our Data Masking Self Assessment Toolkit: